Config2Code simplifies configuration management by automatically generating Python dataclasses from YAML or JSON files. This tool enhances code readability, maintainability, and type safety, saving you time and effort.
Project description
Config2Code: A Tool to Generate Python Dataclasses from Configuration Files
Introduction
Config2Code is a Python tool designed to streamline the process of converting configuration files (YAML or JSON or TOML) into Python dataclasses. By automating the generation of dataclasses, you can improve code readability, maintainability, and type safety.
Installation
You can install Config2Code using pip:
pip install config2code
Usage
Basic Example
-
Prepare your configuration file: Create a YAML or JSON file containing your configuration data. Here's an example YAML file:
DatabaseConfig: host: localhost port: 5432 user: myuser password: mypassword secret: {{database.password}}
-
Run the tool: Use the
config2code
command-line interface to convert the configuration file:config2code to-code --input input.yaml --output output.py
This will generate a Python file
output.py
containing a dataclass representing the configuration:from dataclasses import dataclass @dataclass class DatabaseConfig: host: str port: int user: str password: str secret: str
Placeholder Example
Sometimes you put redundant data in your config file because it is more convenient to only move parts of the config further down the road. Examples could be a machine learning pipeline where you have parameters for your dataset and model which can have redundant values. To counter the problem of always changing multiple values at once in your config we introduce placeholder. A placeholder is a path packed into a token {{<path-in-config>}}
which points to a value you want to insert automatically into your loaded config file. This path starts always at the yaml root and ends at the value to insert.
pipeline:
dataset:
x_dim: 42
y_dim: 5
batch_size: 128
shuffle: True
model:
input_dim: {{pipeline.dataset.x_dim}}
output_dim: {{pipeline.dataset.y_dim}}
activation_func: ReLU
learning_rate: 0.0001
In the case of not having a yaml root you can still use the placeholder with a leading .
inside the token.
dataset:
x_dim: 42
y_dim: 5
batch_size: 128
shuffle: True
model:
input_dim: {{.dataset.x_dim}}
output_dim: {{.dataset.y_dim}}
activation_func: ReLU
learning_rate: 0.0001
Service
This service monitors the requested configuration file. If the services detects changes in the file it will automatically write those changes into the specified output.py
.
You can start the service for example with:
config2code service-start --input input.yaml --output output.py
To stop it you can stop all with
config2code stop-all
Use Config in Code
After you created your python config you can easily use as follows:
from output import DatabaseConfig
config = DatabaseConfig.from_file("input.yaml")
# access config field with dot operator
config.host
Key Features
- Supports YAML, JSON and TOML: Easily convert both formats.
- Automatic dataclass generation: Generates well-structured dataclasses.
- Nested configuration support: Handles nested structures in your configuration files.
- Type inference: Infers types for fields based on their values.
- Placeholder: Choose which values in your config file are dependent on others
Additional Considerations
- Complex data structures: For more complex data structures, consider using custom type hints or additional configuration options.
- Error handling: The tool includes basic error handling for file loading and parsing.
- Future enhancements: We plan to add support for additional file formats, advanced type inference, and more customization options.
Features to expand
- add VS Code extension (create new file on config file save)
- add renaming feature from config to code (renaming a field in the config file should resolve in renaming a field in the code
- add token in config yaml to overwrite field automatically with a dependency on another field (something like
<c2c/2*:dep.config.a/c2c>
) or costum functions<c2c/module.submodule:func(some_value)/c2c>
Contributing
We welcome contributions to improve Config2Code. Feel free to fork the repository, make changes, and submit a pull request.
License
This project is licensed under the MIT License.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file config2class-0.2.1.tar.gz
.
File metadata
- Download URL: config2class-0.2.1.tar.gz
- Upload date:
- Size: 13.4 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.8.4 CPython/3.12.7 Linux/6.8.0-48-generic
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 02473ce30e8eee97f8794271188e08188449cfcedefcdbb4a300dd08ea0b5072 |
|
MD5 | ac0e211bd0f6c5eb9ba59b2bd74e2663 |
|
BLAKE2b-256 | 49fcb8bf250d60fc891c382cbf887d50a4d91d4a128e804e3f0df5ab3789cb16 |
File details
Details for the file config2class-0.2.1-py3-none-any.whl
.
File metadata
- Download URL: config2class-0.2.1-py3-none-any.whl
- Upload date:
- Size: 17.0 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: poetry/1.8.4 CPython/3.12.7 Linux/6.8.0-48-generic
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 59cf9857f2c08542a92b903c7816c1c120417d7b5813b18e16432bddb483ead5 |
|
MD5 | b67237582b021856d824281bb5e71ab2 |
|
BLAKE2b-256 | 0a5d04f0b675d962f795c61f6ef65cb851036d86c3f286d774e242621cb916dd |